In 2009, the South African population was estimated at 49.32 million. The Department of Home Affairs had 612 462 registered deaths in 2006, with approximately 122 492 of these being due to other than natural causes. It is estimated that this number may have remained fairly constant or increased slightly over the past few years. During 2009 and 2010 there were only 35 practising forensic pathologists in South Africa. Furthermore , according to the South African Police Service, over 2 million serious crimes were reported over the 2008-2009 period, whilst there were approximately 153 981 police officers in service. When it is considered that these cases fall within the realm of the forensic pathologists, it should be of great concern that so few qualified specialists exist within the country. South Africa not only has a high occurrence of deaths amongst young adults which can be attributed to trauma and other non-natural causes as well as HIV/AIDS, but urbanisation, an influx of foreigners and an increase in unemployment may also have an influence on the mortality rate of young, working age adults. However, there appears to be a discrepancy in mortality statistics between data released by Statistics South Africa, and the National Population Registry which is maintained by the Department of Home Affairs. This study was undertaken in order to bring about the realisation that professionals are needed in order to bridge a gap in the medico-legal investigation of deaths in South Africa. Approximately half of the cases of sudden unexpected deaths that were reviewed over the fifteen months from January 2009 until March 2010 were due to natural causes, with approximately 37% being signed out as under investigation. In approximately 50% of the cases reviewed, the forensic pathologist was contacted to attend the scene of death, with only half of these scenes being attended by the forensic pathologist on call. Attendance of the post-mortem by the Investigating Officer in charge of the case was poor, with approximately 80% of the post mortem examinations being conducted without the Investigating Officer present. It is believed that medico-legal death investigators would greatly improve the investigation of sudden deaths in South Africa. The institution of medico-legal death investigators would minimise the case load of all the role players, as well as reducing the confusion related with the medico-legal significance of deaths. It is also believed that medico-legal death investigators would minimise and eventually eliminate the gap that currently exists between the departments that are involved with the investigation of deaths. It would thus be advantageous for medico-legal death investigators to fall under the jurisdiction of both the Department of Health and the South African Police Service. / AFRIKAANS : In 2009 was die Suid Afrikaanse bevolking geskat op 49.32 miljoen, in 2006, was daar 612 462 sterftes wat by die Departement van Binnelandse Sake geregistreer is, ongeveer 122 492 was as gevolg van ander dan natuurlike oorsake. Dit kan beraam word dat hierdie getal onveranderd gebly het of effens toegeneem het oor die afgelope paar jaar. Daar was egter net 35 forensiese patoloë wat praktiserend was in Suid Afrika in 2009 en 2010. Verder het die Suid-Afrikaanse Polisiediens berig dat meer as 2 miljoen ernstige misdade gerapporteer was vir die tydperk 2008-2009, terwyl daar net sowat 153 981 poliesiebeamptes in diens was. Wanneer dit beskou word dat hierdie gevalle in die gebied van die forensiese patoloog val, moet dit n groot bekommernis wees dat daar so min bekwaamde spesialiste in die land bestaan. Suid Afrika het 'n hoë voorval van sterftes onder jong volwassenes te danke aan trauma en ander onnatuurlike oorsake sowel as MIV en vigs. Verstedeliking, 'n infloei van binnelanders en 'n toename in werkloosheid kan almal 'n invloed op die sterftesyfer van die jong verkende volwassenes hê. Daar is 'n verskil in mortalitiet statistieke tussen Statistieke Suid Afrika, en die Nasionale Bevolking Register wat in stand gehou word deur die Departement van Binnelandse Sake. Hierdie studie was aangeneem om die verwesenliking uit te voer dat beroepspelers nodig is om die gaping oor te brug wat in die geregtelike mediese ondersoek van sterftes in Suid Afrika plaas vind. Ongeweer halfte van die gevalle van skielike onverwagse sterftes wat vanaf Januarie 2009 oor vyftien maande hersien is, is as gevolg van natuurlike oorsake, terwyl ongeveer 37% onder ondersoek was. In ongeveer die helfte van die gevalle wat hersien was, was die forensiese patoloog gekontak om 'n sterftoneel by te woon, en omtrent net die halfte van hierdie tonele is bygewoon deur die forensiese patoloog. Die bywooning van nadoodse ondersoeke deur die ondersoekbeapte wat toesig oor die geval het was treurig, met ongeveer 80% nadoodse ondersoeke wat gedra was sonder dat die ondersoekbeampte teenwoordig was. Dit is oortuig dat geregtelike mediese doodsondersoekbeamptes die ondersoek van sterftes in Suid Afrika baie sou verminder, die instelling van geregtelike mediese doodsondersoekbeamptes sou die werklos van die rolspelers verminder, sowel as die verrwarring wat verband hou met die geregtelike mediese ondersoek van sterftes verminder. Dit is oortuig dat geregtelike mediese doodsonderdoekbeamptes die gaping wat tans plaasvind met ondersoeke na die sterftes uiteindelik sou uitskakel of verminder, dit sou dus voorledig wees as geregtelike mediese doodsondersoekbeamptes onder die regsgebied van albei die Departement van Binnelandse Sake en die Suid Afrikanse Poliesiediens sou wees. / Dissertation (MSc)--University of Pretoria, 2011. / Forensic Medicine / Unrestricted

In forensic autopsies, accurately estimating the postmortem interval (PMI) is crucial. Traditional methods, relying on physical parameters and police data, often lack precision, particularly after approximately two days have passed since the person's death. New methods are increasingly focusing on analyzing postmortem metabolomics in biological systems, acting as a 'fingerprint' of ongoing processes influenced by internal and external molecules. By carefully analyzing these metabolomic profiles, which span a diverse range of information from events preceding death to postmortem changes, there is potential to provide more accurate estimates of the PMI. The limitation of available real human data has hindered comprehensive investigation until recently. Large-scale metabolomic data collected by the National Board of Forensic Medicine (RMV, Rättsmedicinalverket) presents a unique opportunity for predictive analysis in forensic science, enabling innovative approaches for improving  PMI estimation. However, the metabolomic data appears to be large, complex, and potentially nonlinear, making it difficult to interpret. This underscores the importance of effectively employing machine learning algorithms to manage metabolomic data for the purpose of PMI predictions, the primary focus of this project.  In this study, a dataset consisting of 4,866 human samples and 2,304 metabolites from the RMV was utilized to train a model capable of predicting the PMI. Random Forest (RF) and Artificial Neural Network (ANN) models were then employed for PMI prediction. Furthermore, feature selection and incorporating sex and age into the model were explored to improve the neural network's performance.  This master's thesis shows that ANN consistently outperforms RF in PMI estimation, achieving an R2 of 0.68 and an MAE of 1.51 days compared to RF's R2 of 0.43 and MAE of 2.0 days across the entire PMI-interval. Additionally, feature selection indicates that only 35% of total metabolites are necessary for comparable results with maintained predictive accuracy. Furthermore, Principal Component Analysis (PCA) reveals that these informative metabolites are primarily located within a specific cluster on the first and second principal components (PC), suggesting a need for further research into the biological context of these metabolites.  In conclusion, the dataset has proven valuable for predicting PMI. This indicates significant potential for employing machine learning models in PMI estimation, thereby assisting forensic pathologists in determining the time of death. Notably, the model shows promise in surpassing current methods and filling crucial gaps in the field, representing an important step towards achieving accurate PMI estimations in forensic practice. This project suggests that machine learning will play a central role in assisting with determining time since death in the future.